Search Skills

End-to-end multi-omics data integration and analysis workflow for transcriptomics, proteomics, and metabolomics using MOFA and mixOmics.

Conducts comprehensive quality control for proteomics data, including sample metrics, missing values, batch effects, and intensity distributions.

Validates NGS alignment quality using insert size, GC bias, and strand balance metrics to ensure data integrity before variant calling.

Detects antimicrobial resistance genes in clinical isolates and metagenomic data using AMRFinderPlus, ResFinder, and CARD databases.

Statistically compares cell populations in flow cytometry data to identify significant changes in cell frequencies and marker expression between experimental conditions.

Performs cell segmentation on multiplexed tissue images using deep learning (Cellpose, Mesmer) and classical methods for nuclear and whole-cell analysis in IMC/MIBI data.

Handles Flow Cytometry Standard (FCS) files for loading, parameter access, and initial data exploration in biological data analysis workflows.

Generates pileup data for variant calling using samtools mpileup and pysam, enabling per-position read analysis and allele frequency calculation.

Calls copy number variants (CNV) using GATK best practices for somatic and germline detection from WGS/WES data.

Provides reusable custom plotting functions for omics data analysis, including volcano, MA, PCA, and survival curves using ggplot2 and matplotlib.

Detects bacterial, viral, adapter, and cross-species contamination in sequencing data by screening reads against reference genomes.

Validates PCR primers for specificity, dimers, hairpins, and secondary structures using primer3-py thermodynamic calculations.

Searches biological sequences for motifs and patterns using Biopython, identifying transcription factor binding sites and regulatory elements.

Generates alignment quality statistics and coverage metrics using samtools for genomic data QC reports.

Extracts methylation calls from bisulfite sequencing data in Bismark BAM files, generating per-cytosine reports for CpG, CHG, and CHH contexts.

Selects and applies colorblind-friendly palettes for scientific data visualization using viridis, RColorBrewer, and custom schemes.

Performs linkage disequilibrium analysis including statistics calculation, pruning, haplotype block identification, and visualization for population genetics studies using PLINK and scikit-allel.

Handles phylogenetic tree file operations including parsing, conversion, and multi-tree management across Newick, Nexus, PhyloXML, and NeXML formats using Biopython.

Loads and processes spatial transcriptomics data from Visium, Xenium, MERFISH, Slide-seq, and other platforms using Squidpy and SpatialData, supporting format conversion and spatial coordinate access.

Provides quality assessment metrics for Imaging Mass Cytometry (IMC) data including signal-to-noise, channel correlation, and tissue integrity to ensure reliable analysis and troubleshooting.

Preprocesses imaging mass cytometry (IMC) and MIBI data, including MCD/TIFF handling, hot pixel removal, and image normalization for analysis pipelines.

Merges sample metadata with gene expression count matrices and adds gene annotations for differential expression analysis and visualization.

Polishes genome assemblies using Pilon, Racon, and medaka to reduce errors and improve accuracy in long-read sequencing data.

Identifies peptides and proteins from MS/MS data using database searching, spectral library matching, and FDR estimation.